Print Email Facebook Twitter Axies: Identifying and Evaluating Context-Specific Values Title Axies: Identifying and Evaluating Context-Specific Values Author Liscio, E. (TU Delft Interactive Intelligence) van der Meer, M.T. (Universiteit Leiden) Cavalcante Siebert, L. (TU Delft Interactive Intelligence) Mouter, N. (TU Delft Transport and Logistics) Jonker, C.M. (TU Delft Interactive Intelligence) Murukannaiah, P.K. (TU Delft Interactive Intelligence) Date 2021 Abstract The pursuit of values drives human behavior and promotes cooperation. Existing research is focused on general (e.g., Schwartz) values that transcend contexts. However, context-specific values are necessary to (1) understand human decisions, and (2) engineer intelligent agents that can elicit human values and take value-aligned actions. We propose Axies, a hybrid (human and AI) methodology to identify context-specific values. Axies simplifies the abstract task of value identification as a guided value annotation process involving human annotators. Axies exploits the growing availability of valueladen text corpora and Natural Language Processing to assist the annotators in systematically identifying context-specific values. We evaluate Axies in a user study involving 60 subjects. In our study, six annotators generate value lists for two timely and important contexts: Covid-19 measures, and sustainable Energy. Then, two policy experts and 52 crowd workers evaluate Axies value lists. We find that Axies yields values that are context-specific, consistent across different annotators, and comprehensible to end users. To reference this document use: http://resolver.tudelft.nl/uuid:7d628cb4-0c02-4fc1-a302-3a471b91fcd0 Publisher International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC ISBN 9781450383073 Source Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems Event 20th International Conference on Autonomous Agentsand Multiagent Systems, 2021-05-03 → 2021-05-07, Virtual/online event due to COVID-19 Series AAMAS '21, 2523-5699 Part of collection Institutional Repository Document type conference paper Rights © 2021 E. Liscio, M.T. van der Meer, L. Cavalcante Siebert, N. Mouter, C.M. Jonker, P.K. Murukannaiah Files PDF p799.pdf 1.77 MB Close viewer /islandora/object/uuid:7d628cb4-0c02-4fc1-a302-3a471b91fcd0/datastream/OBJ/view